Evidence map›Paper›PMID 32366008›Full record

ArticleMaterials (Basel, Switzerland)2020

Si-Fe-C-N Coatings for Biomedical Applications: A Combinatorial Approach.

Charlotte Skjöldebrand, Gry Hulsart-Billström, Håkan Engqvist, Cecilia Persson

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Charlotte SkjöldebrandDepartment of Materials Science and Engineering, Faculty of Science and Technology, Uppsala University, 752 37 Uppsala, Sweden.ORCID 0000-0001-5000-5959
Gry Hulsart-BillströmDepartment of Surgical Sciences, Faculty of Medicine and Pharmacy, Uppsala University, 751 83 Uppsala, Sweden.
Håkan EngqvistDepartment of Materials Science and Engineering, Faculty of Science and Technology, Uppsala University, 752 37 Uppsala, Sweden.
Cecilia PerssonDepartment of Materials Science and Engineering, Faculty of Science and Technology, Uppsala University, 752 37 Uppsala, Sweden.ORCID 0000-0001-6663-6536

Funding

Seventh Framework Programme GA-310477
6 · The paper itself

Abstract

Ceramic coatings may prolong the lifetime of joint implants. Certain ions and wear debris may however lead to negative biological effects. SiN-based materials may substantially reduce these effects, but still need optimization for the application. In this study, a combinatorial deposition method enabled an efficient evaluation of a range of Si-Fe-C-N coating compositions on the same sample. The results revealed compositional gradients of Si (26.0-33.9 at.%), Fe (9.6-20.9 at.%), C (8.2-13.9 at.%) and N (39.7-47.2 at.%), and low oxygen contaminations (0.3-0.6 at.%). The mechanical properties varied with a hardness (H) ranging between 13.7-17.3 GPa and an indentation modulus (M) between 190-212 GPa. Both H and M correlated with the Si (H and M increased as Si increased) and Fe (H and M decreased as Fe increased) content. A slightly columnar morphology was observed in cross-sections, as well as a surface roughness in the nm range. A cell study revealed adhering pre-osteogenic MC3T3 cells, with a morphology similar to that of cells seeded on a tissue culture plastic control. The investigated coatings could be considered for further investigation due to the ability to tune their mechanical properties while maintaining a smooth surface, together with their promising in vitro cell response.

Indexed as

biocompatibilitycarboncoatingimplantironmechanical propertiessilicon nitridesurface roughness

Identifiers

PMID32366008
PMCPMC7254256

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.